The cellular telecommunications industry has been rapidly expanding since its inception, and is likely to continue at a phenomenal rate for at least the next few decades. Digital wireless connectivity for both voice and Internet access has experienced particularly high demand in the cellular market. Accordingly, the demand for higher user connectivity and for higher data rates continues. The problem of adding more cellular users can be solved by two fundamentally different approaches. One method is to reduce the cell size, increasing the total number of cells. This approach requires the installation of more cellular base stations. Another method is to employ more sophisticated signal processing to enable more efficient use of the available spectrum to accommodate multiple users.
There are two widely known approaches to multi-user access, that is how to share a single frequency allocation among multiple users within a cell, in digital wireless communications: time division multiple access (TDMA), and code division multiple access (CDMA). TDMA, used for GSM (Global System for Mobile) phones, is currently the most popular approach. In this approach, each user in a cell takes a turn in time. While one user is transmitting, all other users in the cell remain quiet. In CDMA, used by Qualcomm (IS-95), users transmit simultaneously, in the same frequency allocation. The signal for a given user is disentangled from all others by using its unique spreading sequences. The next generation of cellular phone systems (3G) will use CDMA.
In a multiuser spread spectrum system, such as a CDMA (Code Division Multiple Access) system, wireless transmissions are received simultaneously from many users. Any single transmission can be reflected from a variety of objects, causing the same transmission to be received in a multiple, overlapping forms of varying signal strength at various delays and at various angles of arrival. Multiple arrivals arising from a single transmission are often called multipath. The spreading code assigned to each user can be used to identify individual signals, but the fact that many users are received simultaneously (cochannel interference) means that extracting the information content from each transmission is difficult. Signals are distinguished from each other by spreading codes, and by patterns in multipath delays and angles of arrival. Techniques that exploit these differences can be used to mitigate cochannel interference. For example, angular (spatial) separations between signals can be exploited by using arrays of antenna elements, which are sensitive to angles of arrival. Temporal differences between signals due to spreading codes and multipath can also be exploited with or without the use of antenna arrays. Both spatial and temporal interference suppression are computationally intensive. Accordingly, it is generally infeasible to perform both spatial and code mitigation while maintaining acceptable communication throughput in a wireless communication system.
For multiaccess wireless communication systems such as CDMA, given a set of user spreading codes and multiple antenna elements, coefficients of a space-time beamformer are adjusted and the beamformer outputs are processed to estimate data symbols. Each data symbol is remodulated using estimates of the multipath for that symbol and subtracted from the received antenna signals to provide temporal mitigation of interference for other users of the wireless communication system. The space-time beamforming and temporal mitigation of interference are iterated until the estimates of data symbols converge in the sense of a predetermined decision criteria. The same demodulation techniques can be employed in multiple input (more than one transmit antenna), multiple output (multiple receive antennas) MIMO links whether or not a single user or a network or users are involved.
In such a wireless communication system, wireless transmissions are received at one or more antennas. Accordingly, the same transmission may be received at multiple antennas. Further, the wireless transmission may be reflected or refracted from obstacles in the transmission path such that the same transmission is received at multiple delayed times that differ at each antenna. The receiver utilizes a beamformer that combines various delayed versions of the output from each antenna in order to provide the most reliable data decision for a particular user. Each user requires a different beamformer. The spreading code is used to determine the beamformer coefficients by correlating with the delayed outputs. Prior to beamforming, the antenna outputs may have had other users temporally mitigated. Thus the beamfomer only needs to mitigate residual power from other users that are known to the wireless system (known spreading codes) or unknown (users in adjacent cells).
In a multi-user system, transmissions of other users are also be received by the antenna. For each user in turn, the remaining users constitute interference that must be mitigated in order to demodulate successfully. Mitigation can occur through spatial filtering based on multiple antenna elements, through linear temporal filtering based on spreading codes and multipath delay patterns, and through nonlinear temporal filtering based on feedback from the demodulation of interfering cochannel signals. Previous data decisions, correct or not correct, are used in conjunction with estimates of multipath delays in order to mitigate cochannel signals. Mitigation occurs by remodulating the demodulated data in accordance with the spreading code of the signals and estimated multipath delay pattern. The resulting signals (all but the signal currently being demodulated) are subtracted from the antenna outputs, which are then fed to an adaptive space-time beamformer whose output is demodulated to form the estimated data of the signal currently being demodulated. Each signal, in turn, is demodulated in this fashion. When all signals have been demodulated. The process is iterated until a convergence criterion is satisfied. The exact manner in which signals are subtracted from the antennas varies according the iteration and convergence criterion.
The spreading code can also be indicative of the particular data symbol transmitted. Spreading codes are known in the wireless industry and are represented by various industry standards such as IS-95. In an IS-95 CDMA transmission, one of 64 symbols may be received, each symbol using a different, but related, spreading code. The symbol is demodulated, in principle, by correlating the output of the space-time beamformer with each of the candidate spreading codes. The largest correlation selects a spreading code, constituting demodulation.
In CDMA systems, users are physically distributed away from the antenna at various distances. Typically, users from more remote locations tend to be received as more attenuated signals. Similarly, signals from nearby users are typically received with less attenuation. Some wireless systems vary the signal power level to accommodate attenuation. In such systems, however, a transmission having a greater received power level can cancel transmissions of a lower received power level. For this reason, precise base station power level regulation must be employed such that all transmissions, or delayed signals, are received within an acceptable power spread, or range. Each iteration of the multichannel multiuser detector described above successfully demodulates more and more signals. Signals tend to be successfully demodulated in the order of received power, taking into account beamforming gain and multipath. It is often advantageous for the basestation to set received power levels in such a manner that convergence is accelerated.
In the invention as defined by the present claims, the transmissions corresponding to interfering users are processed as interference rather than noise. Rather than ignoring the signals corresponding to other users, as in typical prior art systems, interfering signals received at multiple antenna elements and multiple delays are demodulated and subtracted from the antenna elements, leaving in principle, only the signals corresponding to the user of interest. Both spatial and temporal structures of the data are exploited in the signal processing. By treating the transmissions of other users as interference, rather than noise, sensitivity to precise power level regulation is avoided, since the stronger signals are more easily separated from the weaker signals and are eventually mitigated when the weaker signals are demodulated. In this manner, interference from other users is intelligently mitigated, in contrast to traditional approaches which ignore the effects of in-cell and out-of-cell interference by treating these effects as noise.